In [1]:
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
df = pd.read_csv('scores.csv')
df.head(18)
Out[1]:
Place Car Num Team Penalty Cost Score Presentation Score Design Score Acceleration Score Skid Pad Score Autocross Score Endurance Score Efficiency Score Total Score
0 1 44 Univ of Illinois - Urbana Champaign 0 87.4 40.1 150 76.4 48.2 121.0 275.0 56.1 854.2
1 2 119 Villanova Univ 0 67.3 58.4 115 94.8 53.1 111.1 238.1 100.0 837.8
2 3 67 Univ of Florida 0 58.7 49.2 135 100.0 40.7 123.4 229.7 58.8 795.5
3 4 54 Kettering Univ 0 66.2 49.1 100 85.6 45.4 121.7 205.0 70.6 743.6
4 5 96 University of Alabama - Tuscaloosa 0 65.1 64.1 100 85.2 59.2 111.7 184.9 61.9 732.1
5 6 52 Purdue Univ - W. Lafayette 0 72.6 74.8 135 59.9 66.2 109.5 146.0 64.4 728.4
6 7 68 Louisiana State Univ 0 65.2 53.6 80 77.6 70.8 117.7 184.9 57.0 706.7
7 8 115 Univ of Akron 0 69.7 47.7 115 51.5 30.9 94.9 211.8 64.1 685.7
8 9 48 North Carolina State Univ - Raleigh 0 74.5 60.5 105 73.3 57.1 57.4 190.8 60.1 678.6
9 10 104 Univ of Connecticut 0 80.3 32.2 100 0.0 40.3 123.2 233.3 48.3 657.5
10 11 55 Oklahoma State Univ 0 75.2 40.7 80 76.5 33.3 90.4 173.0 86.8 656.0
11 12 65 Univ of Nebraska - Lincoln 0 77.2 40.4 100 50.2 44.0 100.6 189.3 46.8 648.6
12 13 106 Univ of Waterloo 0 77.4 72.7 100 60.9 23.0 99.9 134.3 73.0 641.1
13 14 83 Hope College 0 71.0 46.4 60 61.9 48.0 79.3 187.8 65.2 619.7
14 15 146 Technische Universitat Berlin 0 79.5 71.5 148 36.2 75.0 123.5 7.0 76.9 617.6
15 16 95 Saginaw Valley State Univ 0 52.0 50.6 70 68.9 45.9 103.2 173.7 46.5 610.8
16 17 63 Univ of Kansas - Lawrence 0 40.3 67.0 80 55.9 8.0 95.4 187.5 43.2 577.3
17 18 150 Univ of North Florida 0 61.1 42.9 80 37.8 54.8 87.8 155.1 49.7 569.1
In [2]:
df = df[df['Cost Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Cost Score',  color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Cost', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[61.1], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
In [3]:
df = pd.read_csv('scores.csv')
df = df[df['Presentation Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Presentation Score',  color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Presentation', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[42.9], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
In [4]:
df = pd.read_csv('scores.csv')
df = df[df['Design Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Design Score',  color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Design', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[80.0], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
In [5]:
df = pd.read_csv('scores.csv')
df = df[df['Acceleration Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Acceleration Score',  color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Acceleration', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[37.8], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
In [6]:
df = pd.read_csv('scores.csv')
df = df[df['Skid Pad Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Skid Pad Score',  color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Skid Pad', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[54.8], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
In [7]:
df = pd.read_csv('scores.csv')
df = df[df['Autocross Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Autocross Score',  color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Autocross', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[87.8], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
In [8]:
df = pd.read_csv('scores.csv')
df = df[df['Endurance Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Endurance Score',  color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Endurance', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[155.1], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
In [9]:
df = pd.read_csv('scores finished endurance.csv')
df = df[df['Endurance Score'] != 0]
df = df.dropna(subset = ['Total Score'])
df = df.sort_values(by=['Total Score'], ascending=True)
fig = px.scatter(df, x = "Total Score", y = 'Endurance Score',  color = "Team", trendline = "ols", trendline_scope="overall", trendline_color_override = 'white', title = 'Total vs Endurance', template = "plotly_dark")
fig.add_trace(go.Scatter(x=[569.1], y=[155.1], name="University of North Florida", marker_symbol = 'star-dot', marker_size = 11 ))
fig.show()
In [ ]: